code: def draw_box(img, results, class_label, scale_x, scale_y):
      label_list = list(
          map(lambda x: x.strip(), open(class_label, "r").readlines())
      )
  
      for i in range(len(results)):
          print(label_list[int(results[i][0])], ":", results[i][1])
          bbox = results[i, 2:]
          label_id = int(results[i, 0])
          score = results[i, 1]
          if score > 0.20:
              xmin, ymin, xmax, ymax = [
                  int(bbox[0] * scale_x),
                  int(bbox[1] * scale_y),
                  int(bbox[2] * scale_x),
                  int(bbox[3] * scale_y),
              ]
              cv2.rectangle(
                  img, (xmin, ymin), (xmax, ymax), (0, 255, 0), 3
              )
              font = cv2.FONT_HERSHEY_SIMPLEX
              label_text = label_list[label_id]
              cv2.rectangle(
                  img, (xmin, ymin), (xmax, ymin - 60), (0, 255, 0), -1
              )
              cv2.putText(
                  img,
                  "#" + label_text,
                  (xmin, ymin - 10),
                  font,
                  1,
                  (255, 255, 255),
                  2,
                  cv2.LINE_AA,
              )
              cv2.putText(
                  img,
                  str(round(score, 3)),
                  (xmin, ymin - 40),
                  font,
                  0.8,
                  (255, 255, 255),
                  2,
                  cv2.LINE_AA,
              )
      return img
  
file_path: PaddleDetection/deploy/third_engine/demo_openvino/python/openvino_benchmark.py
imports: import cv2
  import numpy
  import time
  import argparse
  from scipy.special import softmax
  from openvino.runtime import Core
label_desc: Use image node_id 2 for calling a global function with example usage: draw_box(img, results, class_label, scale_x, scale_y) and returns: img